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xiaobenyang-com

Berlin-Search-Service

get_service_details

get_service_details

Retrieve comprehensive Berlin administrative service details including requirements, forms, fees, and appointment information using a service ID.

Instructions

Get detailed information about a specific Berlin service by its ID. Returns comprehensive information including requirements, forms, fees, appointments, and more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
service_idYes

Implementation Reference

  • Core handler logic shared by all tools, including "get_service_details". Posts tool name as 'func' header and arguments to remote API, formats response as MCP content.
    const calcXiaoBenYangApi = async function (fullArgs: Record<string, any>) {
        // 发起 POST 请求
        let response = await fetch('https://mcp.xiaobenyang.com/api', {
            method: 'POST',
            headers: {
                'XBY-APIKEY': apiKey,
                'func': fullArgs.toolName,
                'mcpid': mcpID
            },
            body: new URLSearchParams(fullArgs)
        });
        const apiResult = await response.text();
    
        return {
            content: [
                {
                    type: "text",
                    text: apiResult // 将字符串结果放入 content 中
                }
            ]
        } as { [x: string]: unknown; content: [{ type: "text"; text: string }] };
    };
  • Tool handler wrapper that adds toolName to arguments and calls the core API executor. Called by the registered lambda for each tool.
    const handleXiaoBenYangApi = async (args: Record<string, any>, toolName: string) => {
        // 校验aid是否存在
        if (toolName === undefined || toolName === null) {
            throw new Error("缺少必要参数 'aid'");
        }
        // 合并参数
        const fullArgs = {...args, toolName: toolName};
        // 调用API
        return calcXiaoBenYangApi(fullArgs);
    };
  • src/mcp.ts:50-65 (registration)
    Registers individual tools with MCP server using name, description, Zod schema, and generic handler lambda.
    const addToolXiaoBenYangApi = function (
        name: string,
        desc: string,
        params: Record<string, ZodType>
    ) {
        server.registerTool(
            name,
            {
                title: name,
                description: desc,
                inputSchema: params,
            }
            ,
            async (args: Record<string, any>) => handleXiaoBenYangApi(args, name)
        )
    };
  • Constructs Zod schema from remote JSON schema properties, mapping types and handling required/optional fields.
    const zodDict: Record<string, z.ZodTypeAny> = {};
    
    Object.entries(inputSchema.properties).forEach(([name, propConfig]) => {
        let zodType;
        let pt = (propConfig as { type: string }).type;
        switch (pt) {
            case 'string':
                zodType = z.string();
                break;
            case 'number':
                zodType = z.number();
                break;
            case 'boolean':
                zodType = z.boolean();
                break;
            case 'integer':
                zodType = z.int32();
                break;
            case 'array':
                zodType = z.array(z.any());
                break;
            case 'object':
                zodType = z.object(z.any());
                break;
            default:
                zodType = z.any();
        }
    
        if (inputSchema.required?.includes(name)) {
            zodDict[name] = zodType;
        } else {
            zodDict[name] = zodType.optional();
        }
    });
  • src/mcp.ts:90-132 (registration)
    Dynamic registration loop: fetches tool list from remote for mcpID, builds schema for each, and registers using addToolXiaoBenYangApi. This registers "get_service_details" if present in remote config.
    for (const apiDesc of apiDescList) {
        let inputSchema = JSON.parse(apiDesc.inputSchema);
        const zodDict: Record<string, z.ZodTypeAny> = {};
    
        Object.entries(inputSchema.properties).forEach(([name, propConfig]) => {
            let zodType;
            let pt = (propConfig as { type: string }).type;
            switch (pt) {
                case 'string':
                    zodType = z.string();
                    break;
                case 'number':
                    zodType = z.number();
                    break;
                case 'boolean':
                    zodType = z.boolean();
                    break;
                case 'integer':
                    zodType = z.int32();
                    break;
                case 'array':
                    zodType = z.array(z.any());
                    break;
                case 'object':
                    zodType = z.object(z.any());
                    break;
                default:
                    zodType = z.any();
            }
    
            if (inputSchema.required?.includes(name)) {
                zodDict[name] = zodType;
            } else {
                zodDict[name] = zodType.optional();
            }
        });
    
    
        addToolXiaoBenYangApi(
            apiDesc.name,
            apiDesc.description ? apiDesc.description : apiDesc.name,
            zodDict);
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool returns 'comprehensive information including requirements, forms, fees, appointments, and more,' which gives some context on output content. However, it lacks details on error handling (e.g., invalid ID), rate limits, authentication needs, or whether it's a read-only operation. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds valuable context about return content. Both sentences earn their place by providing essential information without redundancy or fluff. It's efficient and well-structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a read operation with 1 parameter) and lack of annotations and output schema, the description is minimally complete. It covers the purpose and output scope but misses behavioral details like error cases or authentication. It's adequate for basic use but has clear gaps that could hinder an agent in edge cases or integration scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter with 0% description coverage, so the description must compensate. It adds meaning by specifying that 'service_id' refers to 'a specific Berlin service,' clarifying the parameter's purpose beyond the schema. However, it doesn't detail the ID format (e.g., numeric, string pattern) or provide examples. Since there's only one parameter, the description does a good job of contextualizing it, earning a baseline 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get detailed information about a specific Berlin service by its ID.' It specifies the verb ('Get'), resource ('Berlin service'), and key constraint ('by its ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_services_stats' or 'list_services' beyond mentioning 'detailed information' versus potentially summary views.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_services' (for browsing) or 'search_services' (for filtering), nor does it specify prerequisites such as needing a valid service ID. Usage is implied by the need for detailed info on a known service, but no explicit context or exclusions are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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